Personalizing Product Recommendations While Protecting Privacy

Imagine you’re looking for a birthday gift for a close friend. You know they like gardening, so you order a durable pair of gardening gloves and a decorative plant pot. Fast forward several days, and you’re still seeing recommendations for gardening supplies on unrelated websites, social media feeds, and e-commerce platforms. Where did these advertisers even get your browsing data? While you appreciate a little personalization to help streamline your shopping decisions, this is going too far. It doesn’t feel helpful; it feels intrusive.

This experience is all too common. Customers, by and large, want personalization—71% expect personalized experiences and 76% feel frustrated when brands fail to deliver.¹ Yet, only 27% are comfortable with companies using unsolicited data to achieve the level of customization they demand.² Many consumers are skeptical about how personalization works, and as many as 75% find some forms of personalization downright creepy.³ This tension between the consumer's desire for personalization and their privacy concerns is known as the personalization paradox. For marketing professionals and product teams that want to drive engagement with personalized product recommendations, balancing accuracy with privacy is no easy feat. 

When personalization feels invasive, it backfires. Consumers frequently reject product recommendations when they feel manipulated. Meanwhile, a lack of transparency in how algorithms work, unclear benefits to the end-user, and perceptions of data privacy risks can breed distrust, prompting users to opt out of data collection entirely. 

The missing component in many personalization strategies is psychological privacy. Even when business leaders take steps to ensure data privacy, consumers can still feel vulnerable when confronted with pushy recommendations, targeted advertising, and data collection requests. How can companies provide engaging and relevant recommendations without scaring consumers away? In this article, we examine how behavioral science concepts, such as identity congruence, transparency cues, cognitive fluency, social proof, and reciprocity, can contribute to the development of personalization systems that are both effective and ethical.